Bounteous, Inc. salaries
Median $118,100 across 22 filings for IT roles, Jul 2023 to Jun 2026.
Calculate take-home pay on the calculator pageMedian
$118,100
Middle 50%
$106,200–$150,000
Filings
22
- Median is 8% below the median for all IT roles ($128,000).
- Most filings are wage Level III (36%).
- Software Developers has the most filings (14), with a median of $125,000.
Based on 22 filings. Small samples can differ from actual pay ranges.
Salaries by role
| Role | Filings | Median |
|---|---|---|
| Software Developers | 14 | $125,000 |
| Computer Occupations, All Other | 3 | $107,000 |
| Data Scientists | 2 | $93,800 |
| Software Quality Assurance Analysts and Testers | 2 | $96,600 |
| Database Architects | 1 | $157,000 |
Top metros
| Metro | Filings | Median |
|---|---|---|
| Atlanta-Sandy Springs-Roswell, GA | 3 | $87,900 |
| Chicago-Naperville-Elgin, IL-IN | 2 | $148,800 |
| Dallas-Fort Worth-Arlington, TX | 2 | $129,700 |
| Memphis, TN-MS-AR | 2 | $96,600 |
| New York-Newark-Jersey City, NY-NJ | 2 | $168,500 |
| Raleigh-Cary, NC | 2 | $133,700 |
| Austin-Round Rock-San Marcos, TX | 1 | $132,300 |
| Baltimore-Columbia-Towson, MD | 1 | $125,000 |
| Boston-Cambridge-Newton, MA-NH | 1 | $120,000 |
| Detroit-Warren-Dearborn, MI | 1 | $125,000 |
Level I 14%
Level II 27%
Level III 36%
Level IV 23%
Take-home pay
| Gross | $118,100 |
| Federal income tax | $17,200 |
| Social Security | $7,300 |
| Medicare | $1,700 |
| State income tax | $0 |
| Health insurance (employee share) | $1,400 |
| Take-home per year | $90,500 |
| Take-home per month | $7,500 |
Tax year 2026, single filer.
Local taxes, 401(k), and filing status other than single are not included.
Tax rates checked against IRS, Tax Foundation, and other original sources on Oct 28, 2026.
This is an estimate. Actual taxes depend on your situation. Consult a tax professional before filing.
LCA filings are not hires.
Filed wages are offered base pay, not total compensation.
We did not independently verify the source files. Deduplication and filtering can cause differences from the original data.